Machine vision systems are rapidly becoming the standard way of automating routine visual tasks such as inspection and reading. The systems operate by capturing an image, converting the image into bits of data, and processing that data. In converting an image into data, early machine vision systems simplified the image into one with only two intensity levels--black and white. Such "binary" systems thus discarded much information. More advanced machine vision systems process all of the shades of grey present in an image and consequently have more information on which to base their decisions. This paper explains how grey-scale and binary processing differ. It shows that for accurate, consistent performance, true grey-scale systems are superior.